These files are used to define and deploy Dev and Prod Azure Machine Learning environments. With the default deployment, config-infra-prod.yml will be used when working with the main branch or your ...

Now, the MLOps team can seamlessly manage two Azure Machine Learning environments—one for development, another for production—and the CI/CD pipeline makes deployments directly. The new solution has ...

Azure Arc is Microsoft's offering for allowing customers to bring Azure services and management to any infrastructure, including AWS and Google Cloud. This year, during the virtual Ignite conference, ...

Azure Percept gives you access to affordable hardware that’s ready to work with containerized machine learning models, with a focus on a limited set of scenarios.

All of the major cloud services now offer machine learning and deep learning development environments. On AWS, that’s primarily Amazon SageMaker, which I reviewed in May 2018.On the Google Cloud ...

“We use Azure Machine Learning and PyTorch in our new framework to develop and move AI models into production faster, in a repeatable process that allows data scientists to work both on-premises and ...

Azure Machine Learning is comprehensive, giving users end-to-end capabilities, extensive ML platform abilities in Azure, which empowers data scientists and developers with a wide range of ...

To spot faults quickly even if they take a month to show up, Azure feeds signals into a machine learning system: in the future, you will be able to do that for your own cloud workloads.

Machine learning has become fundamental to many software development projects. This means software engineers need to work with data scientists, adding complexity to their projects.

At the upcoming Visual Studio Live!@ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will lead the session "Predicting the Future using Azure Machine Learning," ...